Query Generation for Patent Retrieval with Keyword Extraction based on Syntactic Features

Open Access
Authors
Publication date 2018
Host editors
  • M. Palmirani
Book title Legal Knowledge and Information Systems
Book subtitle JURIX 2018: The Thirty-first Annual Conference
ISBN
  • 9781614999348
ISBN (electronic)
  • 9781614999355
Series Frontiers in Artificial Intelligence and Aplications
Event JURIX 2018 : 31st International Conference on Legal Knowledge and Information Systems
Pages (from-to) 210-214
Publisher Amsterdam: IOS Press
Organisations
  • Faculty of Science (FNWI)
  • Faculty of Economics and Business (FEB) - Amsterdam Business School Research Institute (ABS-RI)
  • Faculty of Economics and Business (FEB)
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract This paper describes a new method to extract relevant keywords from patent claims, as part of the task of retrieving other patents with similar claims (search for prior art). The method combines a qualitative analysis of the writing style of the claims with NLP methods to parse text, in order to represent a legal text as a specialization arborescence of terms. In this setting, the set of extracted keywords are yielding better search results than keywords extracted with traditional method such as tf-idf. The performance is measured on the search results of a query made of the keywords.
Document type Conference contribution
Language English
Published at https://doi.org/10.3233/978-1-61499-935-5-210
Downloads
FAIA313-0210 (Final published version)
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